The present invention relates generally to the field of organizing unstructured data, and more particularly to constructing a populated graph based on morphological rules applied to semantic models.
Data sets, accumulated by businesses or organizations over time, can become very large and complex. Additional information is derivable from analysis of a single large set of data, as opposed to multiple smaller sets with the same total amount of data. Analysis that determines trends, behaviors, correlations, or untapped opportunities, can add significant value to the business or organization.
Unstructured data, or unstructured information, is usually text-based and may not include a pre-defined data model. To determine and extract potential value from unstructured data, a semantic model may be applied. A semantic model is a form of conceptual data modeling, which represents objects or elements of a domain and the relationships between the elements. A semantic model is an additional layer of information that maps data elements and attributes of data elements into concepts that can be meaningfully interpreted without human intervention. Data in a semantic model is typically organized by a pair of objects and the relationship between them. The total set of elements representing concepts of a semantic model, comprise the taxonomy of classes we use to represent the real world. Together the elements and relationships are represented by an ontology—the vocabulary of the semantic model that provides the basis on which user-defined model queries are formed.
In a general sense, semantics is the study of the meaning behind the words. The context of a relationship between elements of a domain provides the information or knowledge of the domain.